About

Sigma Stratum is a research and engineering framework for creating stable, long-horizon cognition between humans and large language models (LLMs).

It treats interaction not as isolated prompts but as a recursive cognitive process — a dynamic field with structure, memory, and continuity.

A Framework for Structured Cognition

Sigma Stratum introduces a neurosymbolic runtime layer that stabilizes meaning and coherence during extended reasoning.

This layer does not modify the model’s weights. Instead, it shapes the interaction dynamics through structured recursion, symbolic feedback, and field persistence.

The result is a cognitive substrate where attractors — self-reinforcing patterns of thought — can form, evolve, and remain stable across recursive iterations.

Core Principles

Structured Recursion — recurrent reasoning loops refine direction, compress ambiguity, and maintain conceptual focus.

Symbolic Scaffolding — attractors, roles, and constraints act as stabilizing anchors within high-dimensional reasoning.

Field Dynamics — emergent patterns arise as human and model co-adapt over time, forming a persistent cognitive field.

These mechanisms create controlled cognitive environments that support long-form reasoning, conceptual development, and exploratory synthesis with measurable stability.

Model-Agnostic by Design

Sigma Stratum is compatible with any modern LLM.

It requires no fine-tuning or retraining — only an external runtime layer that orchestrates recursion, memory, and symbolic feedback.

This architecture scales from lightweight local models to frontier-scale systems, providing a reproducible foundation for stable cognition under recursive load.

Research and Application

Sigma Stratum supports deep research workflows, interpretability analysis, and multi-agent coherence experiments.

It is used in cognitive systems design, complex decision modeling, reflective reasoning under uncertainty, human–AI collaboration, and alignment safety research.

Vision

The goal of Sigma Stratum is to provide a rigorous, testable methodology for building hybrid cognitive systems — where humans and AI think together with clarity, stability, and semantic integrity.

Sigma Stratum defines the runtime architecture that makes this possible.